AI Engineer

• Design, develop, and deploy AI/ML solutions into production environments
• Transform research concepts into robust, maintainable software systems
• Support research and evaluation of new technologies and products to help inform the development of innovative software solutions.
• Evaluate prototype features or components to ensure they meet functional requirements and usability standards.
• Continuously learn new technologies, tools, and development practices to stay up to date with industry trends and team standards.
• Write clean, efficient, and well-documented code, and participate in testing and debugging to ensure software quality and reliability.
• Participate in product development and engineering activities to help identify issues, propose improvements, and support resolution efforts.
• Support production monitoring and continuous improvement

Senior AI Engineer

• Join a vibrant tech company that empowers technical teams for international and Greek clients.
• Work in diverse, dynamic teams on cutting-edge solutions with global leaders.
• Embrace new ideas and adapt to dynamic environments as part of your local team in Athens.
• Deliver innovative solutions while evolving through projects and supported by an environment based on trust, respect, and empowerment.

• Develop novel reinforcement learning algorithms to solve complex, real-world problems.
• Integrate Large Language Models (LLMs) to enhance agent reasoning, threat intelligence, or human-machine interactions.
• Implement and extend Message Control Protocol (MCP) to enable coordinated behavior across modular AI components or multi-agent systems.
• Prototype new methods and help transition successful prototypes into deployed solutions.
• Collaborate with cross-functional teams (Data Science, Engineering, Product) to integrate and deploy RL models in production.
• Conduct thorough evaluations of model performance using appropriate experimental design and statistical analysis.
• Write clean, maintainable and well-documented code.
• Participate in code reviews and ensure the code quality of your team.
• Troubleshoot and debug complex software issues.

Machine Learning Engineer

• Design, build, and optimize AI‑driven agents and autonomous workflows
• Develop, fine‑tune, and evaluate machine learning models for production use
• Architect and implement data pipelines, model‑serving infrastructure, and agent orchestration components
• Lead experimentation, research, and prototyping of new AI techniques and agent frameworks
• Collaborate with cross‑functional teams to integrate AI capabilities into applications and platforms
• Ensure performance, reliability, and scalability of deployed models and agent systems
• Contribute to technical strategy and mentor other engineers in AI/ML best practices

AI/ML Engineer – Agent Specialist

• **What Your Day Might Look Like:**
• - **Make AI production-ready:** Design and maintain the infrastructure that takes ML models from experimentation to reliable, scalable deployment.
• - **Build automated ML pipelines:** Create repeatable workflows for training, evaluation, deployment, and retraining — with versioning and reproducibility built in.
• - **Deploy and serve models:** Package models as production services across cloud, on-premise, or hybrid environments, with performance and reliability in mind.
• - **Monitor what matters:** Track model performance, data drift, system health, and production signals to support better retraining and troubleshooting decisions.
• - **Enable AI teams:** Work closely with Data Scientists, AI Engineers, and Software Engineers to improve how models are tested, deployed, and maintained.
• - **Set the standard:** Contribute to best practices around CI/CD, model registry, observability, security, and governance.
• - **Support GenAI at scale:** Help deploy and optimize LLM-based systems, including inference services, GPU usage, and RAG infrastructure where needed.
• - **Keep systems secure and reliable:** Ensure ML deployments follow strong practices around access control, data governance, and operational resilience.

Senior MLOps Engineer

• **What Your Day Might Look Like:**
• - **Build AI magic:** Design and develop AI workflows and/or models in Python, with a focus on leveraging LLMs. You will learn how to bridge AI/ML and the Software Engineering world, building scalable AI solutions.
• - **Team collaboration:** Work closely with data scientists, developers, and domain experts to brainstorm ideas, share updates, and guide progress.
• - **Stay ahead:** Research new trends and integrate cutting-edge techniques into your projects.
• - **Problem-solving:** Translate business needs into practical ML/AI solutions, while communicating results clearly.
• - **Document everything:** Ensure your work is reproducible and easily understood across the team.

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AI/ML Engineer – Agent Specialist

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